{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "from pathlib import Path\n",
    "import json\n",
    "from tqdm import tqdm\n",
    "import re\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "import matplotlib.pyplot as plt\n",
    "from glob import glob"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "E = pd.read_csv(\"results2/deepseek_chat_res_HKVPN_eng.csv\")\n",
    "S = pd.read_csv(\"results2/deepseek_chat_res_HKVPN_simp_chinese.csv\")\n",
    "T = pd.read_csv(\"results2/deepseek_chat_res_HKVPN_trad_chinese.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "E_mu  = E.mean()\n",
    "S_mu  = S.mean()\n",
    "T_mu  = T.mean()\n",
    "\n",
    "E_sg  = E.sem()\n",
    "S_sg  = S.sem()\n",
    "T_sg  = T.sem()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define default colors and alpha values\n",
    "default_colors = {\n",
    "    \"DeepSeek Chat\": \"darksalmon\",\n",
    "    \"OpenAI GPT-4o\": \"peachpuff\",\n",
    "    \"Mistral AI\": \"slateblue\",\n",
    "    \"xAI Grok\": \"slategrey\"\n",
    "}\n",
    "\n",
    "default_alpha = {\n",
    "    \"DeepSeek Chat\": 0.8,\n",
    "    \"OpenAI GPT-4o\": 0.8,\n",
    "    \"Mistral AI\": 0.75,\n",
    "    \"xAI Grok\": 0.85\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sig 3\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "countries = [\"Taiwan\", \"USA\", \"UN\", \"HK\", \"China\", \"Russia\",][::-1]\n",
    "qs  = [\"RQ1_{}\".format(i) for i in countries]\n",
    "qs2 = [q for q in E_mu.index if \"RQ4\" in q][:-2]\n",
    "# qs = qs + [\"RQ4_Xi_Jinping\"]\n",
    "E_mu[qs]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "countries = [\"Taiwan\", \"USA\", \"UN\", \"HK\", \"China\", \"Russia\",][::-1]\n",
    "qs = [\"RQ1_{}\".format(i) for i in countries]\n",
    "qs += [q for q in E_mu.index if \"RQ4\" in q][:-2]\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "w = 0.2\n",
    "\n",
    "plt.bar(np.arange(len(qs))-1.5*w, E_mu[qs], width=w, color =  \"darksalmon\", label = \"English\", \n",
    "        edgecolor='black', linewidth=1)\n",
    "plt.bar(np.arange(len(qs))-0.5*w, S_mu[qs], width=w, color =  \"cornflowerblue\",  label = \"Simplified\", \n",
    "        edgecolor='black', linewidth=1, hatch=\"/\")\n",
    "plt.bar(np.arange(len(qs))+0.5*w, T_mu[qs], width=w, color =  \"gold\",  label = \"Traditional\" , \n",
    "        edgecolor='black', linewidth=1, hatch=\"\\\\\",)\n",
    "\n",
    "plt.errorbar(np.arange(len(qs))-1.5*w, E_mu[qs], yerr = E_sg[qs]*3,linestyle='none',color=\"k\")\n",
    "plt.errorbar(np.arange(len(qs))-0.5*w, S_mu[qs], yerr = S_sg[qs]*3,linestyle='none',color=\"k\")\n",
    "plt.errorbar(np.arange(len(qs))+0.5*w, T_mu[qs], yerr = T_sg[qs]*3,linestyle='none',color=\"k\")\n",
    "\n",
    "# plt.ylim(0,5)\n",
    "\n",
    "plt.title(\"b) DeepSeek favorability across languages\", fontsize=20)\n",
    "\n",
    "\n",
    "plt.xticks(np.arange(len(qs)), countries + [\"Xi\", \"Biden\", \"Trump\", \"Putin\",], fontsize=20)\n",
    "plt.yticks(fontsize=20)\n",
    "plt.grid(axis='y', linestyle='--', alpha=0.7)\n",
    "plt.ylabel(\"Favorability\", fontsize=24)\n",
    "\n",
    "plt.legend(fontsize=16)\n",
    "\n",
    "plt.savefig(\"figures/deepseek_language_2.png\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
